Dataset Information

Sacroiliac Joint Asymmetry Regarding Inflammation and Bone Turnover: Assessment by FDG and NaF PET/CT.

ABSTRACT: Objectives:This study was undertaken to determine the role of computed tomography (CT)-based methodology to segment the SI joint and quantify the metabolic activity using positron emission tomography (PET). We measured tracer uptake in the right and left SI joints independently to look for differences between the two sides. Further, we correlated tracer uptake with BMI and studied the inter-observer variation with regard to estimated tracer uptake in the SI joints. Methods:In this retrospective study, a total of 103 subjects (48 females, 55 males) from the CAMONA study database collected 2012-2016 at Odense University Hospital in Denmark were included. Mean age was 48±14.59 years, mean BMI was 26.68±4.31 kg/m2. The SI joints were segmented on fused PET/CT images using a 3D growing algorithm with adjustable upper and lower Hounsfield Units (HU) thresholds. The metabolic activities on the two sides were correlated with BMI. Results:For FDG, we found a higher average SUVmean on the right side (right: 1.3±0.33, left: 1.13±0.30; <0.0001). Similarly, for NaF, the uptake was higher on the right side (right: 5.9±1.29, left: 4.27±1.23; <0.0001). Positive correlations were present between BMI and FDG uptake (P<0.01) as well as NaF uptake (P<0.01). Conclusion:The PET-based molecular imaging probes along with the CT-based segmentation techniques revealed a significant difference in the metabolic activity between the two SI joints with higher inflammation and reactive bone formation on the right side. FDG and NaF uptakes correlated significantly and positively with BMI.

SUBMITTER: Al-Zaghal A

PROVIDER: S-EPMC6661309 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Sacroiliac Joint Asymmetry Regarding Inflammation and Bone Turnover: Assessment by FDG and NaF PET/CT.

Al-Zaghal Abdullah A Yellanki Dani P DP Kothekar Esha E Werner Thomas J TJ Høilund-Carlsen Poul F PF Alavi Abass A

Asia Oceania journal of nuclear medicine & biology 20190101 2

<h4>Objectives</h4>This study was undertaken to determine the role of computed tomography (CT)-based methodology to segment the SI joint and quantify the metabolic activity using positron emission tomography (PET). We measured tracer uptake in the right and left SI joints independently to look for differences between the two sides. Further, we correlated tracer uptake with BMI and studied the inter-observer variation with regard to estimated tracer uptake in the SI joints.<h4>Methods</h4>In this ...[more]

PMID: 31380449

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Project description:INTRODUCTION:Compartmental modelling is an established method of quantifying 18F-FDG uptake; however, only recently has it been applied to evaluate pulmonary inflammation. Implementation of compartmental models remains challenging in the lung, partly due to the low signal-to-noise ratio compared to other organs and the lack of standardisation. Good reproducibility is a key requirement of an imaging biomarker which has yet to be demonstrated in pulmonary compartmental models of 18F-FDG; in this paper, we address this unmet need. METHODS:Retrospective subject data were obtained from the EVOLVE observational study: Ten COPD patients (age =66±9; 8M/2F), 10 ?1ATD patients (age =63±8; 7M/3F) and 10 healthy volunteers (age =68±8; 9M/1F) never smokers. PET and CT images were co-registered, and whole lung regions were extracted from CT using an automated algorithm; the descending aorta was defined using a manually drawn region. Subsequent stages of the compartmental analysis were performed by two independent operators using (i) a MIAKATTM based pipeline and (ii) an in-house developed pipeline. We evaluated the metabolic rate constant of 18F-FDG (Kim) and the fractional blood volume (Vb); Bland-Altman plots were used to compare the results. Further, we adjusted the in-house pipeline to identify the salient features in the analysis which may help improve the standardisation of this technique in the lung. RESULTS:The initial agreement on a subject level was poor: Bland-Altman coefficients of reproducibility for Kim and Vb were 0.0031 and 0.047 respectively. However, the effect size between the groups (i.e. COPD, ?1ATD and healthy subjects) was similar using either pipeline. We identified the key drivers of this difference using an incremental approach: ROI methodology, modelling of the IDIF and time delay estimation. Adjustment of these factors led to improved Bland-Altman coefficients of reproducibility of 0.0015 and 0.027 for Kim and Vb respectively. CONCLUSIONS:Despite similar methodology, differences in implementation can lead to disparate results in the outcome parameters. When reporting the outcomes of lung compartmental modelling, we recommend the inclusion of the details of ROI methodology, input function fitting and time delay estimation to improve reproducibility.

Project description:BACKGROUND:An inflammatory reaction in the airways and lung parenchyma, comprised mainly of neutrophils and alveolar macrophages, is present in some patients with chronic obstructive pulmonary disease (COPD). Thoracic fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) has been proposed as a promising imaging biomarker to assess this inflammation. We sought to introduce a fully quantitative analysis method and compare this with previously published studies based on the Patlak approach using a dataset comprising 18F-FDG PET scans from COPD subjects with elevated circulating inflammatory markers (fibrinogen) and matched healthy volunteers (HV). Dynamic 18F-FDG PET scans were obtained for high-fibrinogen (>2.8 g/l) COPD subjects (N?=?10) and never smoking HV (N?=?10). Lungs were segmented using co-registered computed tomography images and subregions (upper, middle and lower) were semi-automatically defined. A quantitative analysis approach was developed, which corrects for the presence of air and blood in the lung (qABL method), enabling direct estimation of the metabolic rate of FDG in lung tissue. A normalised Patlak analysis approach was also performed to enable comparison with previously published results. Effect sizes (Hedge's g) were used to compare HV and COPD groups. RESULTS:The qABL method detected no difference (Hedge's g?=?0.15 [-0.76 1.04]) in the tissue metabolic rate of FDG in the whole lung between HV (??=?6.0?±?1.9?×?10-3 ml cm-3 min-1) and COPD (??=?5.7?±?1.7?×?10-3 ml cm-3 min-1). However, analysis with the normalised Patlak approach detected a significant difference (Hedge's g?=?-1.59 [-2.57 -0.48]) in whole lung between HV (??=?2.9?±?0.5?×?10-3 ml cm-3 min-1) and COPD (??=?3.9?±?0.7?×?10-3 ml cm-3 min-1). The normalised Patlak endpoint was shown to be a composite measure influenced by air volume, blood volume and actual uptake of 18F-FDG in lung tissue. CONCLUSIONS:We have introduced a quantitative analysis method that provides a direct estimate of the metabolic rate of FDG in lung tissue. This work provides further understanding of the underlying origin of the 18F-FDG signal in the lung in disease groups and helps interpreting changes following standard or novel therapies.

Project description:18F-FDG-PET(/CT) is increasingly used in studies aiming at quantifying atherosclerotic plaque inflammation. Considerable methodological variability exists. The effect of data acquisition and image analysis parameters on quantitative uptake measures, such as standardized uptake value (SUV) and target-to-background ratio (TBR) has not been investigated extensively.The goal of this study was to explore the effect of several data acquisition and image analysis parameters on quantification of vascular wall 18F-FDG uptake measures, in order to increase awareness of potential variability.Three whole-body emission scans and a low-dose CT scan were acquired 38, 60 and 90 minutes after injection of 18F-FDG in six rheumatoid arthritis patients with high cardiovascular risk profiles.Data acquisition (1 and 2) and image analysis (3, 4 and 5) parameters comprised:1. 18F-FDG uptake time, 2. SUV normalisation, 3. drawing regions/volumes of interest (ROI's/VOI's) according to: a. hot-spot (HS), b. whole-segment (WS) and c. most-diseased segment (MDS), 4. Background activity, 5. Image matrix/voxel size.Intraclass correlation coefficients (ICC's) and Bland Altman plots were used to assess agreement between these techniques and between observers. A linear mixed model was used to determine the association between uptake time and continuous outcome variables.1. Significantly higher TBRmax values were found at 90 minutes (1,57 95%CI 1,35-1,80) compared to 38 minutes (1,30 95%CI 1,21-1,39) (P = 0,024) 2. Normalising SUV for BW, LBM and BSA significantly influences average SUVmax (2,25 (±0,60) vs 1,67 (±0,37) vs 0,058 (±0,013)). 3. Intraclass correlation coefficients were high in all vascular segments when SUVmax HS was compared to SUVmax WS. SUVmax HS was consistently higher than SUVmax MDS in all vascular segments. 4. Blood pool activity significantly decreases in all (venous and arterial) segments over time, but does not differ between segments. 5. Image matrix/voxel size does not influence SUVmax.Quantitative measures of vascular wall 18F-FDG uptake are affected mainly by changes in data acquisition parameters. Standardization of methodology needs to be considered when studying atherosclerosis and/or vasculitis.

Dataset Information

Sacroiliac Joint Asymmetry Regarding Inflammation and Bone Turnover: Assessment by FDG and NaF PET/CT.

Publications

Sacroiliac Joint Asymmetry Regarding Inflammation and Bone Turnover: Assessment by FDG and NaF PET/CT.

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